4. Purushothaman,P., “Reinforced Concrete Structural Elements”, 3

Purushothaman,P., “Reinforced Concrete Structural Elements”,. 3 rd. Edition, Tata Mc Graw- Hill Publishing Co, 2004. 5. Pillai and Devadas Menon, “ Re...

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4. Purushothaman,P., “Reinforced Concrete Structural Elements”, 3rd Edition, Tata Mc Graw- Hill Publishing Co, 2004. 5. Pillai and Devadas Menon, “Reinforced Concrete Design”, 2nd Edition, Tata McGraw Hill Publishing Co. Ltd., 2003. 11 GVPCE(A) M.Tech. Structural Engineering 2014 STRUCTURAL OPTIMIZATION Course Code: 13CE 2202

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Course Outcomes: At the end of the course the student will be able to CO1 : Describe problem formulation for a given structure and learn to analysis by classical methods. CO2 : Prepare solutions for non-linear problems. CO3 : Discuss the basics and application of Genetic Algorithm for structurs. CO4 : Explain the concept of Simulated Annealing technique in structurs. CO5 : Use Artificial Neural Networks in structural application. UNIT – I Formulation of Structural Optimization problems: Design variables - Objective function – constraints. Classical methods of optimization for multivariable with equality or inequality constraints: solution by method of Lagrange Multiplier Applications in structural engineering, Kuhn-Tucker conditions. UNIT – II Nonlinear Programming: Unconstrained and Constrained Optimization - Direct search and gradient methods- Basic approach of the Penalty function method - Interior penalty function method and Exterior penalty function method – design of three bar truss, space truss, welded beam design, etc. UNIT – III Genetic Algorithms: – Introduction – basic concept – working principle - Binary coding- Fitness function - Genetic Operators Application to Two bar pendulum, 3-bar truss, optimum fibre orientation, Genetic Algorithms applications to discrete size variables. UNIT – IV

Simulated Annealing: problem formulation- steps involved in SAapplication to RCC retaining wall, and pre-stressed concrete structure design, etc.

GVPCE(A)

12 M.Tech. Structural Engineering

2014

UNIT – V Artificial Neural Networks based approaches for structural optimization problems- Introduction- basic concept of ANNArchitectures and learning methods of NN- Back propagation networks- structural applications. TEXT BOOKS 1. Rao, S.S. “Engineering Optimization, Theory and Applications”, 3rd Edition, New Age International publication, New Delhi, 2010. 2. Rajasekaran, S. and Vijaya Lakshmi Pai, G.A. “Newral networks, Fuzzy logic, and genetic Algorithms, Synthesis and Application”, 1st Edition, PHI, 2003

REFERENCES 1. Arora, J.S. “Introduction to Optimum Design”, 2nd Edition, McGraw-Hill Book Company, 2000. 2. MorrIs A.J., “Foundations of Structural Optimization - A Unified Approach”, 3rd Edition, John Wiley and Sons, 2003.

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